Hi André,
Yes, that's one way to do it. If you already have a single ltraj with all
individuals (one individual per burst), you can simply give it the ltraj
alone. With a single ltraj, the function looks for the closest point in
other bursts. Check the example of the function.
Note that I do not guarantee that my function is efficient! This is R:
there is no use of spatial indexes or bounding boxes, so that for each
point, distances are computed to all other points in the temporal window.
Depending on your data, I guess it could be fairly slow...
Again, if you're looking for performance and/or robustness, I would give a
try to PostGIS here.
Mathieu.
Le 22/07/2015 15:31, André Zehnder a écrit :
Thank you for all your answers!
@ Krzysztof: Yes, I think an approximated method that uses only the nearest
points to compute the distance will suffice. When I include a threshold that
ensures that only temporal differences smaller than xy minutes are taken into
consideration, reasonable results should be achievable.
@ Sarah: I think you are referring to the simulation of a Brownian motion by
the function simm.bb() for an exact solution? I could not find a function that
directly computes the distances. Or did I miss something?
@ Jeremy: Thanks for the hint! A also stumbled upon the pathFrechet() /
distFrechet() function of longitudinalData but rejected them because they seem
not to include the temporal dimension. However, this seems to be only an
erroneous information of inside-r. When I looked at the official reference
manual I saw that distFrechet() considers the time as well.
@ Mathieu: That is pretty much what I am intending to do for a first (and
possibly also final) try, thanks! So I need to input the ltray-object of the
first individual as 'from' and the other one as 'to' in order to check the
distances between their closest points, right? I also tried to program
something like that but the result is shockingly time inefficient and might
still contain some errors. So I will probably try out your function tomorrow :)
Best regards
Andre
-----Ursprüngliche Nachricht-----
Von: Mathieu Basille [mailto:basille....@ase-research.org]
Gesendet: Mittwoch, 22. Juli 2015 19:44
An: André Zehnder; R-sig-eco
Cc: Jeremy Chacon; Sarah Goslee
Betreff: Re: [R-sig-eco] Compute the distance between the trajectories of two
animals with varying sampling intervals
As far as I can tell, there is no such function in adehabitatLT. However, I
wrote a function 'closest' [1] in the package 'hab' [2], which specifically
does that: find the closest relocations from ltraj objects. It can work with
only one ltraj, in which case it will look in other bursts, or with two
different ltraj, in which case it will in the other ltraj. Most importantly,
you can define a temporal windows to restrict the search, which may solve your
problem of irregular time (the ltraj do not have to be regular, or on the same
time schedule). It's only Euclidean distance though. Lastly, it works at the
location level, i.e. it's not considering lines (steps). If that's what you're
looking for, I would probably suggest using PostGIS...
Hope this helps,
Mathieu.
[1] https://github.com/basille/hab/blob/master/R/closest.r
[2] https://github.com/basille/hab
Le 22/07/2015 10:09, Jeremy Chacon a écrit :
I bet Sarah's right and adehabitatLT has something, but I also know
that the longitudinalData package can compute distances between two
trajectories including the frechet distance.
http://www.inside-r.org/packages/cran/longitudinalData/docs/pathFreche
t
However, it does not deal with the timing problem. You will have to
roll your own method of aligning the trajectories in time.
On Wed, Jul 22, 2015 at 9:02 AM, Sarah Goslee <sarah.gos...@gmail.com>
wrote:
Try the adehabitatLT package.
On Wed, Jul 22, 2015 at 9:41 AM, André Zehnder
<andrezehn...@hotmail.com>
wrote:
Hi list,
I want to compute the distances between two trajectories that
consist of
a
sequence of point measurements. The trajectories do not have the
same
length
or sampling interval. So, while for animal A, there is a data point
at
15.00
p.m. and another at 15.38 p.m, animal B might have data points at
14.56
p.m.
and 17.02 p.m.
A possible approach would be to connect these point series to
trajectories
and then calculate the distance between the two trajectories at the
sampled
positions of one trajectory (take the sampled position of the second
trajectory that is temporally closest). Are there any packages in R
(or tools outside of R) that allow me to do this? The support of
other
distances
than the Euclidean one (e.g. Fr chet) would be an advantage.
Best regards,
Andre
--
Sarah Goslee
http://www.functionaldiversity.org
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